The determination of three-dimensional datasets using two-dimensional projection images which describe an object to be presented from different projection angles is widely known. To do this an X-ray emitter of an X-ray device follows an imaging trajectory, for example a circular track, with the two-dimensional X-ray projection images being recorded at prespecified projection angles.
In X-ray devices allowing such three-dimensional imaging, especially CT devices, which are used for example for non-destructive material testing or medical angiography, the generated three-dimensional object datasets are often visualized not directly as a three-dimensional view but as two-dimensional sectional images. A sectional image shows the spatial object density of the object under examination on a sectional plane usually selected by the user. Thus for example precise quantitative length or density measurements are made possible. In neuro-radiology bleeding is often detected on sectional images and sectional image information is likewise often used for blood perfusion measurements. Such measurements are impossible or only possible to a limited extent in projection images or in the volumetric views synthesized from the three-dimensional object dataset.
To visualize sections through the object dataset, the object density function does not have to be known in the overall image volume but only on the selected sections. Thus in the article “Interactive GPU-accelerated image reconstruction in cone-beam CT” by Lars Hillebrand et al., Proceedings of the SPIE, Volume 7258 (2009), page 72582A, a method for CT reconstruction by means of filtered backprojection (FBP) is proposed, which computes the object density online shortly before the visualization only on the sectional planes for which the sectional images are to be displayed. No interpolation of the sectional image from a three-dimensional object dataset is thus necessary. The computation is very efficient and can thus deliver interactive updates of the display if the user modifies the sectional position (sectional plane) and/or at least one reconstruction parameter of the filtered backprojection.
In addition to the filtered backprojection, iterative reconstruction is also known as a reconstruction method, which has a number of advantages over filtered backprojection. Thus prior knowledge about the object can elegantly be introduced in iterative methods as an ancillary condition. This prior knowledge, for example about the possible density range of the object, the object extent or assumptions about object structures makes better image quality possible than with filtered backprojection methods.
According to the current prior art however the object density function must always be calculated in the overall image volume when iterative methods are used which despite modern computation hardware is very time-consuming and can thus not be undertaken interactively or in real time. The reconstruction of an individual section as in the above-mentioned article, is not possible.